1. Field of the Invention
The present invention relates to image tracking device and an image tracking method thereof, and more particularly, to an image tracking device capable of memorization and learning and an image tracking method thereof.
2. Description of the Prior Art
In recent years, due to the wide use of video products and the development of image tracking technologies, people's life now is becoming more convenient and safe. Image tracking technologies have wide application which includes traffic monitoring systems, building security and access control monitoring systems, road surveillance systems, home surveillance systems, and human facial recognition systems. With various image tracking technologies, information carried by a video and captured to serve different application-related purposes can be analyzed to identity the features, such as outline and color, of a tracked object, then determine a feature-related variance of the object in the video, and eventually keep tracking the object in the video according to the variance.
The key to image tracking is to calculate a feature-related variance of an object in a video. In general, an object undergoes translation, zooming, blur, rotation, panning, tilting, illumination, and occlusion in the course of image tracking for different reasons. Typical reasons include image noise interference, abrupt change of ambient illumination, poor lens focusing, and man-made mistakes.
Conventional image tracking technologies have a drawback as follows: the aforesaid feature-related variance of an object in a video is calculated solely with a view to determining the current advancing motion or motion trace of the object in the video. That is to say, the conventional image tracking technologies fail to enable memorization and learning of any feature-related variance of the object in the video. Hence, if the object in the video exhibits the same feature-related variance twice or more, the conventional image tracking technologies will not be effective in perceiving that the current feature-related variance thus calculated has ever happened before, and therefore the current advancing motion or motion trace of the object in the video is repeatedly determined in accordance with the feature-related variance calculated twice or more, respectively. As a result, the conventional image tracking technologies have disadvantages, namely a lengthy tracking process and a waste of available resources.
It is desired to overcome the aforesaid drawback of the conventional image tracking technologies, that is, failure to memorize and learn feature-related variances of an object in a video.